Speaker
Description
The decay of radiogenic isotopes—such as uranium, thorium, and potassium—within the Earth generates radiogenic heat, driving Earth's dynamics. These isotopes also produce geo-neutrinos (anti-electron neutrinos), which serve as the only direct means of observing Earth's internal heat content. KamLAND experiment marked the world's first observation of geo-neutrinos in 2005. Since then, KamLAND has observed geo-neutrinos continuously with 1 kt liquid scintillator.
One major challenge in geo-neutrino observations is the reduction of accidental backgrounds. Although likelihood selection has traditionally been employed for this purpose, this study introduces a new method utilizing decision trees, achieving substantial improvements in background removal efficiency.
In this presentation, I will discuss the methods for background reduction using decision trees and Particle Identification (PID) employing neural networks.
| Poster prize | Yes |
|---|---|
| Given name | Taichi |
| Surname | Sakai |
| First affiliation | RCNS,Tohoku University |
| Institutional email | sakai@awa.tohoku.ac.jp |
| Gender | Male |
| Collaboration (if any) | KamLAND collaboration |
